Molecular‐Level Insights into the Diffusion of a Hydrophobic Drug in a Disordered Block Copolymer Micelle by Molecular Dynamics Simulation
Bibliographic record
Abstract
Abstract Previously, all‐atom molecular dynamics (MD) simulations of a single hydrophobic drug molecule in pseudo‐micelles (consisting of one polymer chain surrounded by several water molecules) were used to gain insight into drug diffusion in nano‐sized micelles. Although it was shown that hydrogen bonding dominates the drug diffusivity, it was not clear to what extent a pseudo‐micelle model captures the drug diffusion dynamics in a full micelle. Since drug release from a stable drug‐loaded micelle occurs on very long timescales, all‐atom MD simulations of the drug diffusion are prohibitively costly. To reduce the computational cost, herein, an all‐atom MD simulation is performed starting from a disordered structure of a full Cucurbitacin B (CuB)‐loaded poly (ethylene oxide‐b‐caprolactone) block copolymer micelle in water. It is found that both the CuB and water dynamics yield nonlinear sub‐diffusive mean‐squared displacements, which result from molecular crowding in the micelle environment and extensive hydrogen bonding interactions between the water/CuB molecules and polymer chains. Moreover, it is found that the hydrogen bonding and diffusion dynamics in the pseudo‐micelle are not representative of those in the full micelle. The computational approach used herein is expected to yield molecular‐level information that can aid in understanding in‐vitro drug release data from nano‐sized micelles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".